人类碳酸酐酶相互作用的热力学、动力学和结构参数化,以增强抑制剂的设计。

IF 7.2 2区 生物学 Q1 BIOPHYSICS Quarterly Reviews of Biophysics Pub Date : 2018-01-01 DOI:10.1017/S0033583518000082
Vaida Linkuvienė, Asta Zubrienė, Elena Manakova, Vytautas Petrauskas, Lina Baranauskienė, Audrius Zakšauskas, Alexey Smirnov, Saulius Gražulis, John E Ladbury, Daumantas Matulis
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引用次数: 36

摘要

合理药物设计的目的是利用定量方法开发小分子以优化亲和力。这将促进化合物的发展,这些化合物将特异性地、选择性地、可逆地、高亲和力地与靶蛋白相互作用。目前尚不可能使用计算机(即计算机)方法开发此类化合物,而是在大型化合物文库的高通量筛选搜索中发现先导分子。计算机方法无法提供的主要原因是我们对化合物结构-热力学和结构-动力学相关性的理解不足。需要建立一系列密切相关的蛋白质和化学多样性之间的内在结合参数数据库(例如,结合后的标准吉布斯能(ΔGint)、焓(ΔHint)、熵(ΔSint)、体积(ΔVintr)、热容(ΔCp,int)、结合力(ka,int)和解离率(kd,int))。而药效基团引导化合物文库与共晶结构的结合,有助于解释结构-能量学的关系,合理设计新化合物。这些数据的组装将有助于为化合物绑定的建模提供相关性和训练数据。在这里,我们报告了大量的内在热力学和动力学数据集,包括400多个伯胺化合物与12个催化活性的人类碳酸酐酶(CA)家族结合。热力学参数已确定通过荧光热移法,等温滴定量热法,并通过停流法抑制酶活性。利用表面等离子体共振进行动力学测量。通过解析蛋白质与磺胺的键合质子化反应,确定了蛋白质与磺胺的键合质子化反应的内在热力学和动力学参数。本文报道的化合物结构-热力学和动力学相关性有助于发现具有皮摩尔亲和力、一小时停留时间和百万倍选择性的非目标CA异构体的化合物。药物先导化合物可用于抗癌靶点CA IX和CA XII,抗青光眼CA IV,抗肥胖CA VA和CA VB等同型异构体。结合60种化合物与6种CA异构体结合的85种x射线晶体结构,该数据库应有助于继续发展合理的靶向药物设计原则。
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Thermodynamic, kinetic, and structural parameterization of human carbonic anhydrase interactions toward enhanced inhibitor design.

The aim of rational drug design is to develop small molecules using a quantitative approach to optimize affinity. This should enhance the development of chemical compounds that would specifically, selectively, reversibly, and with high affinity interact with a target protein. It is not yet possible to develop such compounds using computational (i.e., in silico) approach and instead the lead molecules are discovered in high-throughput screening searches of large compound libraries. The main reason why in silico methods are not capable to deliver is our poor understanding of the compound structure-thermodynamics and structure-kinetics correlations. There is a need for databases of intrinsic binding parameters (e.g., the change upon binding in standard Gibbs energy (ΔGint), enthalpy (ΔHint), entropy (ΔSint), volume (ΔVintr), heat capacity (ΔCp,int), association rate (ka,int), and dissociation rate (kd,int)) between a series of closely related proteins and a chemically diverse, but pharmacophoric group-guided library of compounds together with the co-crystal structures that could help explain the structure-energetics correlations and rationally design novel compounds. Assembly of these data will facilitate attempts to provide correlations and train data for modeling of compound binding. Here, we report large datasets of the intrinsic thermodynamic and kinetic data including over 400 primary sulfonamide compound binding to a family of 12 catalytically active human carbonic anhydrases (CA). Thermodynamic parameters have been determined by the fluorescent thermal shift assay, isothermal titration calorimetry, and by the stopped-flow assay of the inhibition of enzymatic activity. Kinetic measurements were performed using surface plasmon resonance. Intrinsic thermodynamic and kinetic parameters of binding were determined by dissecting the binding-linked protonation reactions of the protein and sulfonamide. The compound structure-thermodynamics and kinetics correlations reported here helped to discover compounds that exhibited picomolar affinities, hour-long residence times, and million-fold selectivities over non-target CA isoforms. Drug-lead compounds are suggested for anticancer target CA IX and CA XII, antiglaucoma CA IV, antiobesity CA VA and CA VB, and other isoforms. Together with 85 X-ray crystallographic structures of 60 compounds bound to six CA isoforms, the database should be of help to continue developing the principles of rational target-based drug design.

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来源期刊
Quarterly Reviews of Biophysics
Quarterly Reviews of Biophysics 生物-生物物理
CiteScore
12.90
自引率
1.60%
发文量
16
期刊介绍: Quarterly Reviews of Biophysics covers the field of experimental and computational biophysics. Experimental biophysics span across different physics-based measurements such as optical microscopy, super-resolution imaging, electron microscopy, X-ray and neutron diffraction, spectroscopy, calorimetry, thermodynamics and their integrated uses. Computational biophysics includes theory, simulations, bioinformatics and system analysis. These biophysical methodologies are used to discover the structure, function and physiology of biological systems in varying complexities from cells, organelles, membranes, protein-nucleic acid complexes, molecular machines to molecules. The majority of reviews published are invited from authors who have made significant contributions to the field, who give critical, readable and sometimes controversial accounts of recent progress and problems in their specialty. The journal has long-standing, worldwide reputation, demonstrated by its high ranking in the ISI Science Citation Index, as a forum for general and specialized communication between biophysicists working in different areas. Thematic issues are occasionally published.
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